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基于 1999-2018 年 NHANES 数据的族裔差异与心血管代谢性慢性病的贝叶斯网络模型。

Bayesian network model of ethno-racial disparities in cardiometabolic-based chronic disease using NHANES 1999-2018.

机构信息

Icahn School of Medicine at Mount Sinai, New York, NY, United States.

Beller Tech LLC, New York, NY, United States.

出版信息

Front Public Health. 2024 Oct 15;12:1409731. doi: 10.3389/fpubh.2024.1409731. eCollection 2024.

Abstract

BACKGROUND

Ethno-racial disparities in cardiometabolic diseases are driven by socioeconomic, behavioral, and environmental factors. Bayesian networks offer an approach to analyze the complex interaction of the multi-tiered modifiable factors and non-modifiable demographics that influence the incidence and progression of cardiometabolic disease.

METHODS

In this study, we learn the structure and parameters of a Bayesian network based on 20 years of data from the US National Health and Nutrition Examination Survey to explore the pathways mediating associations between ethno-racial group and cardiometabolic outcomes. The impact of different factors on cardiometabolic outcomes by ethno-racial group is analyzed using conditional probability queries.

RESULTS

Multiple pathways mediate the indirect association from ethno-racial group to cardiometabolic outcomes: (1) ethno-racial group to education and to behavioral factors (diet); (2) education to behavioral factors (smoking, physical activity, and-via income-to alcohol); (3) and behavioral factors to adiposity-based chronic disease (ABCD) and then other cardiometabolic drivers. Improved diet and physical activity are associated with a larger decrease in probability of ABCD stage 4 among non-Hispanic White (NHW) individuals compared to non-Hispanic Black (NHB) and Hispanic (HI) individuals.

CONCLUSION

Education, income, and behavioral factors mediate ethno-racial disparities in cardiometabolic outcomes, but traditional behavioral factors (diet and physical activity) are less influential among NHB or HI individuals compared to NHW individuals. This suggests the greater contribution of unmeasured individual- and/or neighborhood-level structural determinants of health that impact cardiometabolic drivers among NHB and HI individuals. Further study is needed to discover the nature of these unmeasured determinants to guide cardiometabolic care in diverse populations.

摘要

背景

心血管代谢疾病的种族差异是由社会经济、行为和环境因素驱动的。贝叶斯网络提供了一种分析多层次可调节因素和不可调节人口统计学因素与心血管代谢疾病的发生和进展复杂相互作用的方法。

方法

在这项研究中,我们基于美国国家健康和营养检查调查 20 年的数据,学习贝叶斯网络的结构和参数,以探讨介导种族与心血管代谢结果之间关联的途径。通过条件概率查询分析不同因素对不同种族群体心血管代谢结果的影响。

结果

多种途径介导了从种族群体到心血管代谢结果的间接关联:(1)种族群体到教育和行为因素(饮食);(2)教育到行为因素(吸烟、身体活动以及通过收入到饮酒);(3)行为因素到基于肥胖的慢性疾病(ABCD),然后是其他心血管代谢驱动因素。与非西班牙裔黑人(NHB)和西班牙裔(HI)个体相比,非西班牙裔白人(NHW)个体改善饮食和增加身体活动与 ABCD 阶段 4 的概率降低幅度更大。

结论

教育、收入和行为因素介导了心血管代谢结果的种族差异,但传统的行为因素(饮食和身体活动)对 NHB 或 HI 个体的影响不如 NHW 个体。这表明,在 NHB 和 HI 个体中,更多地受到未测量的个体和/或邻里层面健康结构决定因素的影响,这些因素影响心血管代谢驱动因素。需要进一步研究以发现这些未测量决定因素的性质,从而为不同人群的心血管代谢护理提供指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a287/11519814/617ffd904462/fpubh-12-1409731-g001.jpg

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